We propose a novel attention network for document annotation with user-generated tags. The network is designed according to the human reading and annotation behaviour. Usually, users try to digest the title and obtain a rough idea about the topic first, and then read the content of the document. Present research shows that the title metadata could largely affect the social annotation. To better utilise this information, we design a framework that separates the title from the content of a document and apply a title-guided attention mechanism over each sentence in the content. We also propose two semanticbased loss regularisers that enforce the output of the network to conform to label semantics, i.e. similarity and subsumption. We analyse each part of the proposed system with two real-world open datasets on publication and question annotation. The integrated approach, Joint Multi-label Attention Network (JMAN), significantly outperformed the Bidirectional Gated Recurrent Unit (Bi-GRU) by around 13%-26% and the Hierarchical Attention Network (HAN) by around 4%-12% on both datasets, with around 10%-30% reduction of training time.
As social tagging applications continuously gain in popularity, it becomes more and more accepted that models and tools for (re-)organizing tags are needed. Some first approaches are already practically implemented. Recently, activities to edit and organize tags have been described as "tag gardening". We discuss different ways to subsequently revise and reedit tags and thus introduce different "gardening activities"; among them models that allow gradually adding semantic structures to folksonomies and/or that combine them with more complex forms of knowledge organization systems. Moreover, power tags are introduced as tag gardening candidates and the personal tag repository TagCare is presented.
The SCOT(Social Semantic Cloud Of Tags) ontology is to semantically represent the structure and semantics of a collection of tags and to represent social networks among users based on the tags.
The SCOT(Social Semantic Cloud Of Tags) ontology is to semantically represent the structure and semantics of a collection of tags and to represent social networks among users based on the tags.
Part of the allure of classifying things by assigning tags to them is that the user can give free reign to sloppiness. There is no authority —human or computational— passing judgment on the appropriateness or validity of tags, because tags have to mak
Part of the allure of classifying things by assigning tags to them is that the user can give free reign to sloppiness. There is no authority —human or computational— passing judgment on the appropriateness or validity of tags, because tags have to mak
Clarity regarding controlled vocabularies, taxonomies, thesauri, ontologies, and metamodels. With all the scuttlebut going around about folksonomies and tagging, these are important terms to understand. In the process of tagging, it's pretty noticeable
In case you couldn't (or wouldn't *lazy*), we are here to provide the masses (but mostly ourselves) a place to catalog our media collection, whether it be books, DVDs, CDs...
And we're more than just that. We're providing a place for the packrats to commune and orate.
Wanabo helps you build an effective and alternative window into your site using tagging ». Its the easiest way to bring the power of folksonomies and the 2.0 Web to your online presence.
This piece is based on two talks I gave in the spring of 2005 -- one at the O'Reilly ETech conference in March, entitled "Ontology Is Overrated", and one at the IMCExpo in April entitled "Folksonomies & Tags: The rise of user-developed classification." Th
TagCloud is an automated Folksonomy tool. Essentially, TagCloud searches any number of RSS feeds you specify, extracts keywords from the content and lists them according to prevalence within the RSS feeds.
As I <a href="http://blog.pietrosperoni.it/2005/04/12/technorati-tag-rss/">predicted</a>, a service that offers rss feed of technorati tag blog entries has appeared.
S. Pandya, P. Virparia, и R. Chavda. International Journal on Soft Computing, Artificial Intelligence and Applications (IJSCAI), 5 (1):
09 - 15(февраля 2016)